Risk awareness enabled sizing approach for hybrid energy storage system in distribution network

Abstract

This study presents a bi-level optimal sizing approach for hybrid energy storage system (HESS) in distribution network with high share of renewable energy. Differently from the traditional planning methods, the proposed two-level approach can evaluate the investment risks caused by wind power uncertainty. In particular, the upper level describes the financial composition associated with HESS devices investment cost. The lower level searches optimal operation strategies for the minimal cost of each scenario set. The upper-level and lower level models are bridged by CVaR, which measures the conditional tail expectation of lower level costs for the entire scenarios and are involved as the additional item of the upper objective. Moreover, to improve solution efficiency, some of the mathematics transformations including second-order cone programming are adapted to transform the holistic non-linear model into the more effective pattern that can be computed by the commercially available solver. The proposed method can compute the corresponding energy storage capacity based on the assessment of the risk tolerance of investors. Finally, a test system is used to validate the effectiveness of the proposed approaches.